Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.11861/7660
Title: A new model of simulated evolutionary computation-convergence analysis and specifications
Authors: Prof. LEUNG Kwong Sak 
Duan, Qi-Hong 
Xu, Zong-Ben 
Wong C.K. 
Wong C.K. 
Duan Q.-H. 
Xu Z.-B. 
Issue Date: 2001
Publisher: Institute of Electrical and Electronics Engineers Inc.
Source: IEEE Transactions on Evolutionary Computation, 2001, vol. 5 (1), pp. 3 - 16
Journal: IEEE Transactions on Evolutionary Computation 
Abstract: There have been various algorithms designed for simulating natural evolution. This paper proposes a new simulated evolutionary computation model called the abstract evolutionary algorithm (AEA), which unifies most of the currently known evolutionary algorithms and describes the evolution as an abstract stochastic process composed of two fundamental operators: selection and evolution operators. By axiomatically characterizing the properties of the fundamental selection and evolution operators, several general convergence theorems and convergence rate estimations for the AEA are established. The established theorems are applied to a series of known evolutionary algorithms, directly yielding new convergence conditions and convergence rate estimations of various specific genetic algorithms and evolutionary strategies. The present work provides a significant step toward the establishment of a unified theory of simulated evolutionary computation.
Type: Peer Reviewed Journal Article
URI: http://hdl.handle.net/20.500.11861/7660
ISSN: 1089778X
DOI: 10.1109/4235.910461
Appears in Collections:Applied Data Science - Publication

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